Evaluation of Algorithmic Management of Digital Work Platform in Developing Countries

IF 1.3 Q4 AUTOMATION & CONTROL SYSTEMS International Journal of Automation and Control Pub Date : 2020-11-18 DOI:10.5772/intechopen.94524
Olalekan Samuel Ogunleye, B. Kalema
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Abstract

The economy of the Modern Work Platform is becoming increasingly relevant due to the spread of information and communication technology. As a result, digital work has gained popularity as a source of employment, especially in an economy where finding decent work is becoming increasingly difficult. Computer algorithms are now being used to alter and change the way people operate in increasing job specialization, handling large-scale human labour in a distributed manner. In these structures, human works are delegated, supplemented, and analyzed using tracked data and algorithms. Building on emerging algorithmic literature and qualitative examination, this article assesses the mechanisms by which the digital network manages staff in the sense of Uber, Bolt (formerly Taxify). It describes the difference in the degree to which such platforms limit freedoms over schedules and activities relevant to gig work. Based on in-depth interviews with 41 respondents working on different digital media and a survey of 105 staff on the same platform, the study finds that while all digital work platforms use algorithm management to delegate and assess work, substantial cross-platform variation. Uber, the largest network for ride-sharing, exercises a type of control called “algorithmic despotism” that controls the time and activities of staff more strictly than other network distribution firms. We end with a debate on the implications for the future of work of the spectrum of algorithmic power. It also addresses how algorithmic management and data-driven systems can be developed to build an improved workplace with intelligent machines, with implications for future work.
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发展中国家数字化工作平台算法管理评价
由于信息和通信技术的普及,现代工作平台的经济变得越来越重要。因此,数字工作作为一种就业来源越来越受欢迎,尤其是在寻找体面工作变得越来越困难的经济体中。计算机算法现在正被用来改变和改变人们在日益专业化的工作中运作的方式,以分布式的方式处理大规模的人力劳动。在这些结构中,使用跟踪数据和算法对人类工作进行委派、补充和分析。在新兴算法文献和定性研究的基础上,本文评估了数字网络在Uber、Bolt(前身为Taxify)意义上管理员工的机制。它描述了这些平台在与零工工作相关的时间表和活动上限制自由的程度上的差异。基于对41名在不同数字媒体工作的受访者的深度访谈,以及对同一平台上105名员工的调查,该研究发现,尽管所有数字工作平台都使用算法管理来委派和评估工作,但跨平台差异很大。优步是最大的拼车网络,它实行一种被称为“算法专制”的控制,比其他网络分销公司更严格地控制员工的时间和活动。我们以一场关于算法能力频谱对未来工作的影响的辩论结束。它还讨论了如何开发算法管理和数据驱动系统,以建立一个使用智能机器的改进工作场所,并对未来的工作产生影响。
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来源期刊
International Journal of Automation and Control
International Journal of Automation and Control AUTOMATION & CONTROL SYSTEMS-
自引率
41.70%
发文量
50
期刊介绍: IJAAC addresses the evolution and realisation of the theory, algorithms, techniques, schemes and tools for any kind of automation and control platforms including macro, micro and nano scale machineries and systems, with emphasis on implications that state-of-the-art technology choices have on both the feasibility and practicability of the intended applications. This perspective acknowledges the complexity of the automation, instrumentation and process control methods and delineates itself as an interface between the theory and practice existing in parallel over diverse spheres. Topics covered include: -Control theory and practice- Identification and modelling- Mechatronics- Application of soft computing- Real-time issues- Distributed control and remote monitoring- System integration- Fault detection and isolation (FDI)- Virtual instrumentation and control- Fieldbus technology and interfaces- Agriculture, environment, health applications- Industry, military, space applications
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